Evolutionary Genomics & Bioinformatics

Author: “Billy (Peng) Zhou”

Lab1:Introduction to R and Reproducible ResearchFile

Lab2:git, GitHub and Rstudio projectsFile

Lab3A:Data Wrangling:Starting with data

Lab3B Data Wrangling:Manipulating, analyzing and exporting data with tidyverse

Lab4 Data wrangling and graphing COVID-19 reporting data (Part 1)

Lab4A Data visualization with ggplot2 (Part 1)

Lab5 Data wrangling and graphing COVID-19 reporting data (Part 2)

Lab5A Data visualization with ggplot2 (Part 2)

Lab5 extra: Interactive Graphs and Animations from the COVID-19 reporting data

Lab6 Data Maps and Interactive Graphs from the COVID-19 reporting data

Lab6a Plot Display

Lab6b R Shiny apps

Lab7 RNA-Seq workflow: gene-level exploratory analysis and differential expression

Lab8: Sequence Alignment, Phylogenetic Analysis and Tree Visualization

Lab9A : Programming in R - Regular Expressions

Lab9B : Programming in R - Control Structures and Functions

Lab10: Population genomics based on high throughput sequencing (HTS)

Lab 11: Microbiome Analysis using dada2 and phyloseq

Lab 12: Network Analysis using Cytoscape and RCy3

Lab 13 : Sprucing up your Rmarkdown and GitHub Page

Application written in R (R Core Team 2015) using the Shiny framework (Chang et al. 2015).

REFERENCE

Chang, W., J. Cheng, JJ. Allaire, Y. Xie, and J. McPherson. 2015. “Shiny: Web Application Framework for r. R Package Version 0.12.1.” Computer Program. http://CRAN.R-project.org/package=shiny.

R Core Team. 2015. “R: A Language and Environment for Statistical Computing.” Journal Article. http://www.R-project.org.